A sigmoidoscopy-based case–control study of polyps: macronutrients, fiber and meat consumption

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Using a sigmoidoscopy-based case-control study (753 cases, 799 controls) in Los Angeles County, we investigated the potential modifier role in the effect of alcohol and smoking of single-nucleotide polymorphisms (SNP) in three DNA repair genes, XRCC1 (Arg194Trp and Arg399Gln), XRCC3 (Thr241Met), and XPD (Lys751Gln). We have previously reported an inverse association between the XRCC1 codon 399 SNP and adenoma risk among these subjects. We now report that subjects with the XPD Gln/Gln genotype were inversely associated with adenoma risk [odds ratio (OR), 0.7; 95% confidence interval (95% CI), 0.5-1.0] when compared with subjects with the Lys/Lys and Lys/Gln genotypes combined. This association differed between different ethnic groups (gene Â race heterogeneity likelihood ratio test, P = 0.009), with a stronger inverse association among Latinos (OR, 0.1; 95% CI, 0.01-0.5) than among non-Latinos (OR, 0.9; 95% CI, 0.-1.3). We found no evidence of an XRCC3 Â smoking or alcohol interaction or an XRCC1 Â alcohol interaction. Instead, our data supported an XRCC1 Â smoking interaction (P = 0.048). Whereas XPD did not modify the effect of smoking, our data suggested an XPD Â alcohol interaction. Analyses ignoring XPD showed no association between alcohol intake and adenoma prevalence; however, among carriers of the codon 751 Gln/Gln genotype, we found a significant positive association (OR, 2.5; 95% CI, 1.2-5.2 for ever drinkers; test of interaction P = 0.04). Our data suggest that the effects of smoking and alcohol may vary depending on the genetic background of proteins that participate in the base excision repair and nucleotide excision repair pathways. (Cancer Epidemiol Biomarkers Prev 2006;15(12):2384-90)

Section: Resultsmentioning

confidence: 96%

Section: Methodsmentioning

confidence: 99%

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XRCC1, XRCC3, and XPD Polymorphisms as Modifiers of the Effect of Smoking and Alcohol on Colorectal Adenoma Risk

Stern

Siegmund

Conti

et al. 2006

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“…All subjects for this study were participants in a USC/Kaiser study of risk factors for colorectal adenomas and were examined by flexible sigmoidoscopy from 1991 to 1993 (phase I) and 1993 to 1995 (phase II) at either of two southern California Kaiser Permanente Medical Centers (Bellflower and Sunset). Phase I of this study has been previously described (18). Phase II subjects were recruited using the same criteria as phase I.…”

Section: Methodsmentioning

confidence: 99%

XRCC1 and XRCC3 Polymorphisms and Their Role as Effect Modifiers of Unsaturated Fatty Acids and Antioxidant Intake on Colorectal Adenomas Risk

Stern

Siegmund

Corral

et al. 2005

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Whereas animal and in vitro studies support a role of unsaturated fatty acids in colon carcinogenesis, the epidemiologic evidence is inconclusive. Using a large sigmoidoscopy-based case-control study (753 cases and 799 controls) in Los Angeles County, we investigated possible associations between single-nucleotide polymorphisms in the XRCC1 (codons 194 Arg/Trp and codon 399 Arg/Gln) and XRCC3 (codon 241 Thr/Met) genes and colorectal adenoma risk and their possible role as modifiers of the effect of monounsaturated fatty acid, the ratio of N-6/N-3 polyunsaturated fatty acids, and antioxidant intake. We found no evidence of associations between the XRCC1 codon 194 Arg/Trp or Trp/Trp genotypes and the XRCC3 codon 241 Thr/Met or Met/Met genotypes. Subjects with the XRCC1 Gln/Gln genotype were inversely associated with adenoma risk (odds ratio, 0.6; 95% confidence interval, 0.4-0.9; P = 0.01) when compared with subjects with Arg/ Arg and Arg/Gln genotypes combined. We found no evidence of gene-dietary fat interactions for the XRCC3 codon 241 polymorphism. However, our data suggest an XRCC1-unsaturated fat interaction. High monounsaturated fatty acid intake was associated with adenoma risk only among subjects with the XRCC1 codon 194 Arg/Arg and codon 399 Gln/Gln combined genotypes (P for interaction = 0.018). High N-6/N-3 polyunsaturated fatty acid ratios were associated with adenoma risk among subjects with the XRCC1 codon 194 Arg/Arg and codon 399 Gln/Gln or the codon 194 Arg/Trp or Trp/Trp and codon 399 Arg/Arg or Arg/Gln combined genotypes (P for interaction = 0.026). These interactions were not modified by antioxidant intake. However, low antioxidant intake was associated with an inverse association only among subjects with the XRCC1 codon 194 Arg/Trp or Trp/Trp and codon 399 Arg/Arg or Arg/Gln combined genotypes (P for interaction = 0.022), which was independent of unsaturated fat intake. Our data suggest that the XRCC1 codon 194 and codon 399 single nucleotide polymorphisms may modify the effect of unsaturated fatty acid and antioxidant intake and that this XRCC1 effect modification may explain, in part, previously reported inconsistencies on the role of unsaturated fatty acids and adenoma risk.

“…The data reported are from a study of colorectal adenomas (12). Cases were individuals diagnosed for the first time with adenomas confirmed by histology.…”

Section: Methodsmentioning

confidence: 99%

Modeling Exposures for DNA Methylation Profiles

Siegmund¹,

Levine²,

Chang³

et al. 2006

We extend the finite mixture model to estimate the association between exposure and latent disease subtype measured by DNA methylation profiles. Estimates from this model are compared with those obtained from the simpler two-phase approach of first clustering the DNA methylation data followed by associating exposure with disease subtype using logistic regression. The two models are fit to data from a study of colorectal adenomas and are compared in a simulation study. Depending on the analytic approach, we obtain different estimates of the odds ratio (OR) and its 95% confidence interval (95% CI) for the association of RBC folate and DNA methylation subtype in colorectal adenomas (OR, 0.31; 95% CI, 0.08-1.26 from the extended finite mixture model; OR, 0.44; 95% CI, 0.15-1.28 from the twophase approach; n = 58 case subjects). Although our results could be a chance occurrence due to fluctuations from small sample size, we did a simulation study using larger samples and found that differences between the two approaches emerge when there is noise in the cluster analysis. In the naive two-phase approach, the estimate of the OR is biased towards the null, and its SE is underestimated when there is error in the cluster assignment. Estimates from the extended mixture model are unbiased and have the correct SE estimate but may require larger sample sizes for convergence. Thus, when the clusters are not identified with certainty, the extended mixture model is preferred for valid estimation of the OR and CI. (Cancer Epidemiol Biomarkers Prev 2006;15(3):567 -72)